Spatial patterns of within-tree<i>Enaphalodes rufulus</i>(Coleoptera: Cerambycidae) attacks during outbreak conditions in the Ozark National Forest in Arkansas, United States of America
Bibliographic record
Abstract
Abstract Enaphalodes rufulus(Haldeman) (red oak borer; Coleoptera: Cerambycidae) is a native wood borer that colonises and develops in oaks (QuercusLinnaeus; Fagaceae) across southeastern Canada and the eastern United States of America. It is rarely considered a pest because it normally occurs at low population density levels in stressed or dying oak trees. In the late 1990s and early 2000s there was a large, historically unique outbreak ofE.rufulusin the Ozark mountains of Arkansas and Missouri, United States of America. This outbreak provided an opportunity to investigate within-tree spatial distribution of attacks during unusually high insect population levels. Fifty trees from northern Arkansas were felled and destructively sampled. The locations of attack sites by femaleE.rufuluswere standardised across varying heights and diameters for comparison across trees. Attack sites showed a significant clustered pattern within trees. Attack sites were aggregated towards the lower and middle bole, and on the south-facing side of trees. This pattern has been seen in other insects, including wood borers, and is potentially related to differences in temperature. These patterns of ovipositional behaviour in outbreak situations have implications forE.rufulusresource partitioning and facultative intraguild predation among larvae.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".